A mathematical approach to differentiate spontaneous and induced evolution to drug resistance during cancer treatment

Drug resistance is a major impediment to the success of cancer treatment. Resistance is typically thought to arise through random genetic mutations, after which mutated cells expand via Darwinian selection. However, recent experimental evidence suggests that the progression to drug resistance need not occur randomly, but instead may be induced by the treatment itself, through either genetic changes or epigenetic alterations. This relatively novel notion of resistance complicates the already challenging task of designing effective treatment protocols. To better understand resistance, we have developed a mathematical modeling framework that incorporates both spontaneous and drug-induced resistance. Our model demonstrates that the ability of a drug to induce resistance can result in qualitatively different responses to the same drug dose and delivery schedule. We have also proven that the induction parameter in our model is theoretically identifiable, and proposed an in vitro protocol which could be used to determine a treatment’s propensity to induce resistance.